CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks

CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks

5 February 2021

Maartje ter Hoeve

Gabriele Tolomei

Maarten de Rijke

Fabrizio Silvestri

Papers citing "CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks"

18 / 18 papers shown

Title
Robustness questions the interpretability of graph neural networks: what to do? Kirill Lukyanov Georgii Sazonov Serafim Boyarsky Ilya Makarov AAML 41 0 0 05 May 2025
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning Volkan Bakir Polat Goktas Sureyya Akyuz 36 0 0 26 Apr 2025
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks Emré Anakok Pierre Barbillon Colin Fontaine Elisa Thébault 40 0 0 19 Mar 2025
Natural Language Counterfactual Explanations for Graphs Using Large Language Models Flavio Giorgi Cesare Campagnano Fabrizio Silvestri Gabriele Tolomei LRM 27 1 0 28 Jan 2025
GraphXAIN: Narratives to Explain Graph Neural Networks Mateusz Cedro David Martens 29 0 0 04 Nov 2024
Explainable Graph Neural Networks Under Fire Zhong Li Simon Geisler Yuhang Wang Stephan Günnemann M. Leeuwen AAML 21 0 0 10 Jun 2024
Explaining Expert Search and Team Formation Systems with ExES Kiarash Golzadeh Lukasz Golab Jaroslaw Szlichta 18 0 0 21 May 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 19 2 0 19 Dec 2023
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 6 22 0 22 May 2023
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability Indro Spinelli Michele Guerra F. Bianchi Simone Scardapane 17 0 0 14 Apr 2023
GANExplainer: GAN-based Graph Neural Networks Explainer Yiqiao Li Jianlong Zhou Boyuan Zheng Fang Chen LLMAG 19 4 0 30 Dec 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 18 7 0 28 Sep 2022
Evaluating Explainability for Graph Neural Networks Chirag Agarwal Owen Queen Himabindu Lakkaraju Marinka Zitnik 18 99 0 19 Aug 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 34 98 0 16 May 2022
Few-Shot Graph Learning for Molecular Property Prediction Zhichun Guo Chuxu Zhang W. Yu John E. Herr Olaf Wiest Meng-Long Jiang Nitesh V. Chawla AI4CE 102 130 0 16 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 156 463 0 31 Dec 2020
BRPO: Batch Residual Policy Optimization Kentaro Kanamori Yinlam Chow Takuya Takagi Hiroki Arimura Honglak Lee Ken Kobayashi Craig Boutilier OffRL 123 46 0 08 Feb 2020
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 219 3,658 0 28 Feb 2017